With the growing demand for urban freight transportation, trucks emit a large amount of pollutants such as particulate matters and nitrogen oxides, increasingly affecting public health. This study establishes a modelized air dispersion structure to simulate pollutant concentration distribution. By integrating multiple data sources including mobile phone signals and satellite images, we reconstruct the daily trajectories of individuals and further incorporate simulated pollution concentrations in calculating dynamic and static exposure of individuals to truck emissions. Econometric models considering spatial dependence are developed to evaluate the influencing factors and elucidate the mechanisms of pollutant exposure. Results show factors including freight demand, road network, residential and employment locations, personal commuting distance, and population age structure matter in assessing truck emission exposure. As a result, a mixture of vehicular emission standards, urban traffic control, land planning, and industrial policies is proposed to reduce truck pollutant exposure and safeguard public health.